Practical Machine Learning Cookbook

An overview of supervised learning

Supervised learning entails learning a mapping between a set of input variables (typically a vector) and an output variable (also called the supervisory signal) and applying this mapping to predict the outputs for unseen data. Supervised methods attempt to discover the relationship between input variables and target variables. The relationship discovered is represented in a structure referred to as a model. Usually models describe and explain phenomena, which are hidden in the dataset and can be used for predicting the value of the target attribute knowing the values of the input attributes.

Supervised learning is the machine learning task of inferring a function from supervised training data (set of training ...